Nada Mohamed Abbas Ibrahim
@nadamohamedabbas7-hashStatistics graduate skilled in Python, R, and data analysis. Interested in analytics, research, and applied statistics.
Language Breakdown
Lines of code distribution across 6 owned repositories
I-Shaped Developer
I-shapedSpecialist — deep expertise in R
Collaboration Network
Global Impact visualization
Repos
6
PRs
0
Growth
+18%
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Coding Streak
Contribution activity over the past year
mohamed-Dscience
@mohamed-Dscience
mohammedalmogtaba2022-cmd
@mohammedalmogtaba2022-cmd
Momen Mohamed
@Momedn5454093
Top Repositories
This repository contains survival analysis projects using Kaggle datasets, including telecom customer churn and lung cancer survival. It applies Kaplan-Meier curves and Cox proportional hazards models to study time-to-event outcomes, identify key factors affecting survival, and generate predictive insights for retention and clinical outcomes.
This study uses field survey data from Uzbekistan to examine how socio-demographic and attitudinal factors influence political participation. It analyzes age, gender, education, income, residence, and social media use using descriptive and statistical methods to understand patterns of political engagement and democratic involvement.
This study analyzes the 2019 World Happiness data using multivariate statistical methods to identify key drivers of global well-being. After removing outliers, it performs descriptive and correlation analysis, factor analysis to extract two latent dimensions, regression to explain happiness, and clustering to group countries globally.
This repository contains various statistical analysis reports using datasets from Kaggle, covering applied econometric techniques, regression models, and data analysis methods. The projects focus on data cleaning, exploration, model estimation, visualization, and interpretation using diverse sample datasets.
This project analyzes regional differences in consumer behavior across urban, rural, eastern, and western areas. Using sales data, it examines how location influences purchasing preferences and market trends. Despite incomplete raw data, transformation and analysis provide insights to support targeted business and marketing strategies.
This study examines financial inclusion in Egypt (2021–2024), focusing on digital transformation, inequality, and behavioral factors shaping access and resilience. Using World Bank Global Findex data, it applies logistic regression, clustering, decomposition, and structural equation modeling to assess inclusion dynamics for policy insights Egypt.
Open Source Impact
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